Report¶

Introduction¶

  • This dataset encapsulates a comprehensive collection of financial information, spanning multiple stocks within the Nifty 50 index. It comprises a rich array of data points, including stock prices, trading volumes, and related metrics, amassed over a substantial timeframe. This dataset serves as a valuable resource for analyzing market trends, assessing stock performances, and deriving insights crucial for informed investment strategies and comprehensive market evaluations.

  • The Nifty 50 index represents a collection of 50 actively traded Indian stocks listed on the National Stock Exchange (NSE). These stocks are chosen based on various factors like market capitalization, liquidity, and other financial parameters. The index serves as a benchmark for the Indian stock market, reflecting the performance of these select companies across diverse sectors, offering a snapshot of the overall market movements.

  • Regarding the dataset, it encompasses a wide array of financial metrics for stocks within the Nifty 50 index. This includes historical stock prices, trading volumes, market indicators, fundamental ratios, and potentially other relevant data points.

  • Constraints within this dataset might include factors such as:

  1. Timeframe: Data might be available within a specific time range due to historical limitations or data collection constraints.
  2. Availability of Metrics: Some metrics or specific data points might be missing or incomplete due to various reasons, like unreported values or data collection issues.
  3. Accuracy: The dataset's accuracy might be influenced by factors like reporting errors or discrepancies in the data sources.
  4. Granularity: Depending on the source, the dataset might have limitations in granularity, such as daily, weekly, or monthly data, which could impact detailed analysis at a more refined time scale.
  • The dataset's richness and comprehensive nature make it a valuable tool for conducting in-depth analysis, identifying market trends, evaluating stock performances, and formulating informed investment strategies within the context of the Indian stock market
In [1]:
import pandas as pd
import glob
import matplotlib.pyplot as plt
import seaborn as sns

Reading all the CSV files¶

In [2]:
file_list = glob.glob('C:/Users/devan/Desktop/Big Data Analytics/Final Project/*.csv')
data_frames = []
for file in file_list:
    data = pd.read_csv(file)
    data_frames.append(data)
nifty_data = pd.concat(data_frames, ignore_index=True)

This code compiles data from multiple CSV files located in a specified directory. It first collects a list of file paths using 'glob.glob', then reads each CSV file using Pandas' 'read_csv' function and stores the data in a list of data frames. Finally, it merges these separate data frames into a single comprehensive DataFrame named 'nifty_data' using 'pd.concat', providing a consolidated dataset that aggregates information from all the CSV files for streamlined analysis within the context of Big Data Analytics.

In [3]:
nifty_data.head()
Out[3]:
Date Symbol Series Prev Close Open High Low Last Close VWAP Volume Turnover Trades Deliverable Volume %Deliverble Company Name Industry ISIN Code
0 2007-11-27 MUNDRAPORT EQ 440.00 770.00 1050.00 770.0 959.0 962.90 984.72 27294366.0 2.687719e+15 NaN 9859619.0 0.3612 NaN NaN NaN
1 2007-11-28 MUNDRAPORT EQ 962.90 984.00 990.00 874.0 885.0 893.90 941.38 4581338.0 4.312765e+14 NaN 1453278.0 0.3172 NaN NaN NaN
2 2007-11-29 MUNDRAPORT EQ 893.90 909.00 914.75 841.0 887.0 884.20 888.09 5124121.0 4.550658e+14 NaN 1069678.0 0.2088 NaN NaN NaN
3 2007-11-30 MUNDRAPORT EQ 884.20 890.00 958.00 890.0 929.0 921.55 929.17 4609762.0 4.283257e+14 NaN 1260913.0 0.2735 NaN NaN NaN
4 2007-12-03 MUNDRAPORT EQ 921.55 939.75 995.00 922.0 980.0 969.30 965.65 2977470.0 2.875200e+14 NaN 816123.0 0.2741 NaN NaN NaN

What are the data types?¶

In [4]:
nifty_data = nifty_data.astype({'Symbol': 'category'})
nifty_data.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 470434 entries, 0 to 470433
Data columns (total 18 columns):
 #   Column              Non-Null Count   Dtype   
---  ------              --------------   -----   
 0   Date                470384 non-null  object  
 1   Symbol              470434 non-null  category
 2   Series              470434 non-null  object  
 3   Prev Close          470384 non-null  float64 
 4   Open                470384 non-null  float64 
 5   High                470384 non-null  float64 
 6   Low                 470384 non-null  float64 
 7   Last                470384 non-null  float64 
 8   Close               470384 non-null  float64 
 9   VWAP                470384 non-null  float64 
 10  Volume              470384 non-null  float64 
 11  Turnover            470384 non-null  float64 
 12  Trades              240688 non-null  float64 
 13  Deliverable Volume  438230 non-null  float64 
 14  %Deliverble         438230 non-null  float64 
 15  Company Name        50 non-null      object  
 16  Industry            50 non-null      object  
 17  ISIN Code           50 non-null      object  
dtypes: category(1), float64(12), object(5)
memory usage: 61.5+ MB
In [5]:
nifty_data.Symbol.unique()
Out[5]:
['MUNDRAPORT', 'ADANIPORTS', 'ASIANPAINT', 'UTIBANK', 'AXISBANK', ..., 'VEDL', 'WIPRO', 'ZEETELE', 'ZEEL', 'INFRATEL']
Length: 66
Categories (66, object): ['ADANIPORTS', 'ASIANPAINT', 'AXISBANK', 'BAJAJ-AUTO', ..., 'VEDL', 'WIPRO', 'ZEEL', 'ZEETELE']

Finding unique values (stocks) from the dataset.

Descriptive statistics of the dataset.¶

In [6]:
nifty_data.shape
Out[6]:
(470434, 18)
In [7]:
nifty_data.describe()
Out[7]:
Prev Close Open High Low Last Close VWAP Volume Turnover Trades Deliverable Volume %Deliverble
count 470384.000000 470384.000000 470384.000000 470384.000000 470384.000000 470384.000000 470384.000000 4.703840e+05 4.703840e+05 2.406880e+05 4.382300e+05 438230.000000
mean 1266.196349 1267.759708 1286.581440 1247.488465 1266.388302 1266.554351 1267.132300 3.045903e+06 1.610138e+14 6.196427e+04 1.315098e+06 0.502997
std 2581.367576 2585.256861 2619.646432 2546.618689 2581.389799 2582.138197 2582.697234 7.333973e+06 3.298082e+14 6.866443e+04 2.831667e+06 0.190019
min 0.000000 8.500000 9.750000 8.500000 9.100000 9.150000 9.210000 3.000000e+00 1.047000e+07 1.100000e+01 5.000000e+00 0.023600
25% 274.300000 275.000000 279.500000 269.600000 274.400000 274.350000 274.697500 2.190095e+05 1.612816e+13 2.183400e+04 1.253825e+05 0.364700
50% 566.500000 567.025000 576.900000 556.500000 567.000000 566.700000 566.940000 1.010938e+06 6.832603e+13 4.406800e+04 5.017560e+05 0.511000
75% 1242.200000 1243.312500 1263.000000 1221.650000 1242.900000 1242.400000 1242.662500 3.019851e+06 1.863835e+14 7.893550e+04 1.452238e+06 0.638400
max 32861.950000 33399.950000 33480.000000 32468.100000 32849.000000 32861.950000 32975.240000 4.810589e+08 3.564334e+16 1.643015e+06 2.325307e+08 1.000000
  • The descriptive statistics presented here offer insights into various aspects of a financial dataset related to stock market trading. These statistics provide a summary overview of the numerical attributes within the dataset, shedding light on the stock market's price movements and trading volumes.

  • The 'count' row indicates the total number of observations for each column, implying the quantity of available data points for analysis. The 'mean' row showcases the average values for each attribute, providing a central tendency measure for the dataset. Meanwhile, the 'std' row illustrates the standard deviation, signifying the extent of variability or dispersion around the mean.

  • The 'min' and 'max' rows signify the minimum and maximum values observed in each column, outlining the range of values present in the dataset. The '25%', '50%', and '75%' rows correspond to the first quartile (25th percentile), median (50th percentile), and third quartile (75th percentile), respectively. These percentiles offer insights into the distribution and spread of the data, indicating the values below which a certain percentage of observations lie.

  • These descriptive statistics aid in understanding the range, central tendency, and dispersion of stock prices, trading volumes, and related metrics. They facilitate preliminary assessments of data characteristics, aiding analysts and investors in making informed decisions and formulating strategies based on historical market behavior.

Finding null values in the dataset¶

In [8]:
nifty_data.isna().sum()
Out[8]:
Date                      50
Symbol                     0
Series                     0
Prev Close                50
Open                      50
High                      50
Low                       50
Last                      50
Close                     50
VWAP                      50
Volume                    50
Turnover                  50
Trades                229746
Deliverable Volume     32204
%Deliverble            32204
Company Name          470384
Industry              470384
ISIN Code             470384
dtype: int64
In [9]:
nifty_data['Date'] = pd.to_datetime(nifty_data['Date'])
In [10]:
nifty_data['Year'] = nifty_data['Date'].dt.year
nifty_data_yearly = nifty_data.groupby('Year')[['High', 'Low']].mean()
plt.figure(figsize=(10, 6))
bar_width = 0.35
index = nifty_data_yearly.index
plt.bar(index - bar_width/2, nifty_data_yearly['High'], bar_width, color='blue', label='High')
plt.bar(index + bar_width/2, nifty_data_yearly['Low'], bar_width, color='red', label='Low')
plt.title('Nifty 50 Index Changes (2000 - 2021)')
plt.xlabel('Year')
plt.ylabel('Average Nifty 50 Index Value')
plt.legend()
plt.xticks(index)
plt.grid(axis='y')
plt.tight_layout()
plt.show()
  • A visual representation showcasing the annual high-low ranges of the Nifty Fifty through a bar graph provides a comprehensive overview of the market's yearly price volatility.
In [11]:
for stock in nifty_data['Symbol'].unique():
    plt.figure(figsize=(8, 5))  # Each stock gets its own plot
    temp_df = nifty_data[nifty_data['Symbol'] == stock]
    
    # Group data by year and calculate the mean 'Close' and 'Open' values for each year
    yearly_data = temp_df.groupby(temp_df['Date'].dt.year)[['High', 'Low']].mean()
    
    plt.plot(yearly_data.index, yearly_data['High'], marker='o', label='High')
    plt.plot(yearly_data.index, yearly_data['Low'], marker='o', label='Low')
    
    plt.title(f"Nifty 50 Index for '{stock}' (Close and Open) by Year")
    plt.xlabel('Year')
    plt.ylabel('price')
    plt.legend()
    plt.grid(True)
    plt.tight_layout()
    plt.show()
  • This code segment utilizes Python and Matplotlib to generate individual line plots representing the annual mean high and low prices of stocks within the Nifty 50 index. For each unique stock symbol in the dataset, the code creates a distinct plot, adjusting the figure size accordingly.

  • By isolating the data for each stock symbol, the code groups the information by year, calculating the average high and low prices for every year using the 'groupby' function. The resulting line plots display trends in these yearly average high and low prices, showcasing the fluctuation patterns over time for each stock within the Nifty 50 index.

  • This visualization strategy facilitates a clear comparison of how high and low prices have trended annually for different stocks. Investors and analysts can interpret these trends to identify historical patterns, assess market volatility, and gain insights into potential price ranges for various stocks over the years, aiding in informed decision-making and strategic analysis within the realm of stock market investments.

In [12]:
nifty_blank = ['JSWSTL','INFRATEL']
nifty_data[nifty_data['Symbol'].isin(nifty_blank)]
Out[12]:
Date Symbol Series Prev Close Open High Low Last Close VWAP Volume Turnover Trades Deliverable Volume %Deliverble Company Name Industry ISIN Code Year
127798 2005-03-23 JSWSTL EQ 10.00 455.00 458.50 383.60 386.9 390.15 419.86 2087710.0 8.765375e+13 NaN 382057.0 0.1830 NaN NaN NaN 2005.0
127799 2005-03-24 JSWSTL EQ 390.15 392.85 398.50 357.50 371.8 369.20 372.01 1226479.0 4.562638e+13 NaN 232172.0 0.1893 NaN NaN NaN 2005.0
127800 2005-03-28 JSWSTL EQ 369.20 376.70 394.05 375.00 380.0 378.85 383.64 1235794.0 4.741048e+13 NaN 263415.0 0.2132 NaN NaN NaN 2005.0
127801 2005-03-29 JSWSTL EQ 378.85 382.90 383.80 363.25 369.1 368.05 375.26 624072.0 2.341915e+13 NaN 198916.0 0.3187 NaN NaN NaN 2005.0
127802 2005-03-30 JSWSTL EQ 368.05 367.00 371.90 360.05 362.7 362.15 365.13 466349.0 1.702775e+13 NaN 159641.0 0.3423 NaN NaN NaN 2005.0
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
281417 2005-09-12 JSWSTL EQ 282.60 285.00 291.00 285.00 289.0 288.25 288.71 421914.0 1.218089e+13 NaN 271520.0 0.6435 NaN NaN NaN 2005.0
281418 2005-09-13 JSWSTL EQ 288.25 288.50 303.00 287.10 296.6 297.50 295.89 667860.0 1.976153e+13 NaN 399014.0 0.5975 NaN NaN NaN 2005.0
281419 2005-09-14 JSWSTL EQ 297.50 299.00 307.50 291.10 294.3 295.40 301.00 648158.0 1.950985e+13 NaN 291204.0 0.4493 NaN NaN NaN 2005.0
281420 2005-09-15 JSWSTL EQ 295.40 297.00 299.00 294.95 296.0 296.50 297.00 371305.0 1.102761e+13 NaN 216658.0 0.5835 NaN NaN NaN 2005.0
417065 NaT INFRATEL EQ NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Bharti Infratel Ltd. TELECOM INE121J01017 NaN

247 rows × 19 columns

In [13]:
symbols_to_drop = ['JSWSTL', 'INFRATEL']
nifty_data_2 = nifty_data[~nifty_data['Symbol'].isin(symbols_to_drop)]
  • Excluding the symbols 'JSWSTL' and 'INFRATEL' from the dataset due to inadequate available data, aiming to ensure data integrity and analytical robustness throughout the analysis process.

A correlation matrix was generated to analyze the relationships between chosen stocks, outlined and elaborated upon in the report. This matrix provides insights into how the price movements of these stocks relate to each other, aiding in understanding potential patterns or dependencies in their behavior.¶

In [14]:
corr = nifty_data_2[nifty_data_2['Symbol']== 'HEROMOTOCO'].corr() 
plt.figure(figsize=(10,10))
sns.heatmap(corr, annot=True, cmap="coolwarm")
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\4069535145.py:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.
  corr = nifty_data_2[nifty_data_2['Symbol']== 'HEROMOTOCO'].corr()
Out[14]:
<Axes: >
In [15]:
corr = nifty_data_2[nifty_data_2['Symbol']== 'HDFC'].corr() 
plt.figure(figsize=(10,10))
sns.heatmap(corr, annot=True, cmap="coolwarm")
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\728104081.py:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.
  corr = nifty_data_2[nifty_data_2['Symbol']== 'HDFC'].corr()
Out[15]:
<Axes: >
In [16]:
corr = nifty_data_2[nifty_data_2['Symbol']== 'HDFCBANK'].corr() 
plt.figure(figsize=(10,10))
sns.heatmap(corr, annot=True, cmap="coolwarm")
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\83096412.py:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.
  corr = nifty_data_2[nifty_data_2['Symbol']== 'HDFCBANK'].corr()
Out[16]:
<Axes: >
In [17]:
corr = nifty_data_2[nifty_data_2['Symbol']== 'HCLTECH'].corr() 
plt.figure(figsize=(10,10))
sns.heatmap(corr, annot=True, cmap="coolwarm")
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\251171166.py:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.
  corr = nifty_data_2[nifty_data_2['Symbol']== 'HCLTECH'].corr()
Out[17]:
<Axes: >
  • A correlation matrix for stocks such as 'HEROMOTOCO','HDFC', 'HDFC BANK', and 'HCL TECH' enables an extensive analysis of how its price movements align or diverge with other variables. This matrix quantifies the degree and direction of linear relationships between 'HEROMOTOCO' and the mentioned stocks, assigning values from -1 to 1. These values signify the strength and nature of correlations: 1 denotes a perfect positive correlation, -1 represents a perfect negative correlation, and 0 suggests no linear relationship. Such an analysis aids investors and analysts in understanding potential associations or diversifications within a portfolio, facilitating informed decisions based on historical price behaviors and their interconnections.

Assessing the performance of individual stocks from 2000 to 2021 by investing 32,000 INR equally in 2000 and determining the value in 2021. This analysis aims to gauge the growth or decline of the initial investment, providing insights into the long-term returns generated by each stock.¶

In [18]:
invested_amount_2000 = 500
In [19]:
unique_symbols = nifty_data_2['Symbol'].unique()
results_df = pd.DataFrame(columns=['Symbol', 'First_Open_2000','Invested_amount_2000', 'Last_Close_2021', 'Return_Amount_2021','Net_Worth'])
for symbol in unique_symbols:
    symbol_data = nifty_data_2[nifty_data_2['Symbol'] == symbol]
    symbol_data = symbol_data.sort_values(by='Year')
    first_open_value = symbol_data['Open'].first_valid_index()
    first_open = symbol_data.loc[first_open_value, 'Open'] if first_open_value is not None else None
    last_close_value = symbol_data['Close'].last_valid_index()
    last_close = symbol_data.loc[last_close_value, 'Close'] if last_close_value is not None else None
    return_amount_2021 = invested_amount_2000 * last_close / first_open if (first_open is not None and last_close is not None) else None
    net = return_amount_2021 - invested_amount_2000
    results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
In [20]:
results_df
Out[20]:
Symbol First_Open_2000 Invested_amount_2000 Last_Close_2021 Return_Amount_2021 Net_Worth
0 MUNDRAPORT 770.0 500 135.50 87.987013 -412.012987
1 ADANIPORTS 137.1 500 730.05 2662.472648 2162.472648
2 ASIANPAINT 370.0 500 2536.40 3427.567568 2927.567568
3 UTIBANK 26.7 500 597.50 11189.138577 10689.138577
4 AXISBANK 588.0 500 714.90 607.908163 107.908163
... ... ... ... ... ... ...
59 SSLT 185.0 500 220.15 595.000000 95.000000
60 VEDL 218.4 500 257.25 588.942308 88.942308
61 WIPRO 2724.0 500 492.75 90.446035 -409.553965
62 ZEETELE 1175.0 500 238.35 101.425532 -398.574468
63 ZEEL 230.0 500 185.60 403.478261 -96.521739

64 rows × 6 columns

In [21]:
unique_symbols = results_df['Symbol'].unique()
for symbol in unique_symbols:
    symbol_data = results_df[results_df['Symbol'] == symbol]
    plt.figure(figsize=(6, 4))
    plt.bar(['Invested 2000', 'Return 2021'], [symbol_data['Invested_amount_2000'].iloc[0], symbol_data['Return_Amount_2021'].iloc[0]])
    plt.xlabel('Amount')
    plt.ylabel('Value')
    plt.title(f'Invested Amount in 2000 vs Return Amount in 2021 - {symbol}')
    plt.tight_layout()
    plt.show()
In [22]:
results_df['Price_Difference'] = results_df['Last_Close_2021'] - results_df['First_Open_2000']
max_row = results_df.loc[results_df['Price_Difference'].idxmax()]
print("Stock with maximum growth as on 2021:")
print(max_row)
Stock with maximum growth as on 2021:
Symbol                       SHREECEM
First_Open_2000                  68.0
Invested_amount_2000              500
Last_Close_2021               27910.5
Return_Amount_2021      205224.264706
Net_Worth               204724.264706
Price_Difference              27842.5
Name: 46, dtype: object
  • Determining the stock with the highest return.

Calculating the present value of a portfolio evenly distributed across multiple stocks since 2000, starting with an initial investment of 64,000 INR, and assessing its current worth in 2021 to evaluate the overall performance of the investment.¶

In [23]:
invested_amount_2000 = 1000
In [24]:
unique_symbols = nifty_data_2['Symbol'].unique()
results_df = pd.DataFrame(columns=['Symbol', 'First_Open_2000','Invested_amount_2000', 'Last_Close_2021', 'Return_Amount_2021','Net_Worth'])
for symbol in unique_symbols:
    symbol_data = nifty_data_2[nifty_data_2['Symbol'] == symbol]
    symbol_data = symbol_data.sort_values(by='Year')
    first_open_value = symbol_data['Open'].first_valid_index()
    first_open = symbol_data.loc[first_open_value, 'Open'] if first_open_value is not None else None
    last_close_value = symbol_data['Close'].last_valid_index()
    last_close = symbol_data.loc[last_close_value, 'Close'] if last_close_value is not None else None
    return_amount_2021 = invested_amount_2000 * last_close / first_open if (first_open is not None and last_close is not None) else None
    net = return_amount_2021 - invested_amount_2000
    results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
In [25]:
results_df
Out[25]:
Symbol First_Open_2000 Invested_amount_2000 Last_Close_2021 Return_Amount_2021 Net_Worth
0 MUNDRAPORT 770.0 1000 135.50 175.974026 -824.025974
1 ADANIPORTS 137.1 1000 730.05 5324.945295 4324.945295
2 ASIANPAINT 370.0 1000 2536.40 6855.135135 5855.135135
3 UTIBANK 26.7 1000 597.50 22378.277154 21378.277154
4 AXISBANK 588.0 1000 714.90 1215.816327 215.816327
... ... ... ... ... ... ...
59 SSLT 185.0 1000 220.15 1190.000000 190.000000
60 VEDL 218.4 1000 257.25 1177.884615 177.884615
61 WIPRO 2724.0 1000 492.75 180.892070 -819.107930
62 ZEETELE 1175.0 1000 238.35 202.851064 -797.148936
63 ZEEL 230.0 1000 185.60 806.956522 -193.043478

64 rows × 6 columns

In [26]:
plt.figure(figsize=(6, 4))
plt.bar(['Invested 2000', 'Return 2021'], [results_df['Invested_amount_2000'].sum(), results_df['Return_Amount_2021'].sum()])
plt.xlabel('Amount')
plt.ylabel('Value')
plt.title('Invested Amount in 2000 vs Return Amount in 2021')
plt.tight_layout()
plt.show()
In [27]:
results_df['Net_Worth'].sum()-results_df['Invested_amount_2000'].sum()
Out[27]:
648661.901070853
In [28]:
percentage_value = round((results_df['Net_Worth'].sum() - results_df['Invested_amount_2000'].sum()) * 100 / results_df['Invested_amount_2000'].sum(), 2)
result_with_percentage = str(percentage_value) + '%'
result_with_percentage
Out[28]:
'1013.53%'
  • Profit percentage as on year 2021.

Conclusion¶

  • The portfolio exhibited an exceptional growth of 1013.53% from its 2000 inception, translating an initial investment of 64000 INR into a substantial profit of 648661.90 INR by the end of 2021.
  • In summary, diving into this dataset has been eye-opening. We've seen how stock prices and trading volumes vary across different companies in the Nifty 50 index, showing us how the market moves. Looking at correlations between stocks helped us understand how they relate, guiding us on how to spread investments for safety. Plus, simulating past investments gave us a glimpse into potential portfolio growth or decline. Altogether, this data is a goldmine for making smarter investment decisions.